Damage Sensitive Signals for the Assessment of the Conditions of Wind Turbine Rotor Blades Using Electromagnetic Waves

One of the most important renewable energy technologies used nowadays are wind power turbines. In this paper, we are interested in identifying the operating status of wind turbines, especially rotor blades, by means of multiphysical models. It is a state-of-the-art technology to test mechanical structures with ultrasonic-based methods. However, due to the density and the required high resolution, the testing is performed with high-frequency waves, which cannot penetrate the structure in depth. Therefore, there is a need to adopt techniques in the fields of multiphysical model-based inversion schemes or data-driven structural health monitoring. Before investing effort in the development of such approaches, further insights and approaches are necessary to make the techniques applicable to structures such as wind power plants (blades). Among the expected developments, further accelerations of the so-called forward codes for a more efficient implementation of the wave equation could be envisaged. Here, we employ electromagnetic waves for the early detection of cracks. Because in many practical situations, it is not possible to apply techniques from tomography (characterized by multiple sources and sensor pairs), we focus here on the question of whether the existence of cracks can be determined by using only one source for the sent waves.

Automated summary

Wind power turbines are one of the most important renewable energy technologies. This paper focuses on using multiphysical models to identify the operating status of wind turbines, particularly the rotor blades. Due to the limitations of high-frequency waves, there is a need for further research on multiphysical model-based inversion schemes or data-driven structural health monitoring techniques. The development of faster forward codes for implementing the wave equation is also anticipated. The author explores the use of electromagnetic waves for early crack detection and investigates the possibility of determining the existence of cracks using only one source.